发表机构
Leiden University; Leiden University Medical Centre（莱顿大学; 莱顿大学医学中心）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本研究拟开发端到端多语言隐喻处理框架，整合隐喻检测、面向隐喻的翻译评估及联合建模，结合语言学理论与大语言模型，以提升多语言NLP系统处理比喻语言的能力。
AI 中文摘要
隐喻性语言仍是多语言自然语言处理的主要挑战，因为成功的解读与翻译需要超越字面词义的推理。现有研究大多将隐喻检测、机器翻译及翻译评估作为独立任务开展，而极少有工作探索如何将这些组件整合为统一的计算框架。本博士提案旨在开发一个端到端的多语言隐喻处理框架，包含三个互补的研究方向：（1）跨语言的鲁棒隐喻检测；（2）面向隐喻的翻译评估，适用于人工评估与自动质量评估；（3）连接隐喻检测与翻译评估的联合建模。拟议研究将结合语言学理论与大型语言模型的最新进展，开发用于感知隐喻的机器翻译的新数据集、标注方法、评估基准及自动评估方法。预期成果是一个统一框架，可提升处理比喻语言时多语言NLP系统的开发与评估水平。
英文摘要
Metaphorical language remains a major challenge for multilingual natural language processing because successful interpretation and translation require reasoning beyond literal lexical meaning. Existing research has largely investigated metaphor detection, machine translation, and translation evaluation as separate tasks, while little work has explored how these components can be integrated into a unified computational framework. This PhD proposal aims to develop an end-to-end framework for multilingual metaphor processing consisting of three complementary research directions: (1) robust metaphor detection across languages, (2) metaphor-oriented translation evaluation for both human assessment and automatic quality estimation, and (3) joint modelling that connects metaphor detection with translation evaluation. The proposed research will combine linguistic theory with recent advances in large language models to develop new datasets, annotation methodologies, evaluation benchmarks, and automatic evaluation approaches for metaphor-aware machine translation. The expected outcome is a unified framework that improves both the development and evaluation of multilingual NLP systems when processing figurative language.
CommentsScientific report on PhD thesis plans and milestones achieved (current progress)
